Academic Affiliations
  • Professor, Department of Obstetrics and Gynecology, Wayne State University
  • Adjunct Professor, Department of Computer Science, Wayne State University
Education and Training
  • B.Sc. – Chemical Engineering, "Politehnica" University, Bucharest, Romania
  • M.Sc. – Electrochemistry, National Polytechnic Institute of Grenoble, France
  • Ph.D. – Chemical Engineering, Laval University, Quebec, Canada
  • Postdoctoral training – Bioinformatics, Laval University, Quebec, Canada
Research Accomplishments
  • Led the design and implementation of the DREAM Preterm Birth Prediction Challenge to identify transcriptional markers for pregnancy dating and assessment of the risk of spontaneous preterm birth
  • Received multiple top awards in international systems biology/machine learning competitions such as the sbv IMPROVER and DREAM challenges
  • Developed genomics data analysis methods and software packages available in Bioconductor, including:
    • normalization of microarray data (nnNorm)
    • analysis of signaling pathways (SPIA)
    • analysis of gene sets (PADOG)
    • predictive modeling (maPredictDSC)
  • Developed a customized approach to cervical length assessment for the prediction of spontaneous preterm birth
  • Established the PRB/NICHD African American Customized Fetal Growth Standard
  • Developed FetalGPS, a tool to calculate fetal growth percentile for 6 existing standards
  • Created and applied neural network modeling and genetic algorithm optimization approaches to engineering and genomics problems
Awards and Recognitions
  • Top Reviewer of the American Journal of Obstetrics & Gynecology, Feb 2019
  • Ranked in the top 5 in sub-challenges of the DREAM Single Cell Transcriptomics Challenge (, Dec 2018
  • Ranked 1st in the Human blood gene signature as exposure response marker sub-challenge of the IMPROVER Systems Toxicology Challenge, (, May 2016
  • Ranked 1st in the Intra-Species Protein Phosphorylation Prediction sub-challenge of the IMPROVER Species Translation Challenge (, October 2013
  • Best Overall Award, IMPROVER Diagnostic Signature Challenge (, October 2012
Research Interests
  • Personalized medicine, such as customized fetal growth assessment and cervical length evaluation
  • Identification of genomics-based biomarkers for fetal death, preeclampsia, fetal growth restriction, and spontaneous preterm delivery
  • Analytical methods for genomics data analysis and interpretation, such as for pathway and gene set analysis
  • Machine learning and crowdsourcing with multi-omics data to develop robust multi-marker models
  • Single-cell genomics for disease prediction and spatial reconstruction of tissues
Select Publications
  • Gudicha DW, Romero R, Kabiri D, Hernandez-Andrade E, Pacora P, Erez O, Kusanovic JP, Jung E, Paredes C, Berry SM, Yeo L, Hassan SS, Hsu CD, Tarca AL. Personalized assessment of cervical length improves prediction of spontaneous preterm birth: a standard and a percentile calculator. Am J Obstet Gynecol. 2020 Sep 9:S0002-9378(20)31059-0.
  • Tarca AL, Romero R, Xu Z, Gomez-Lopez N, Erez O, Hsu CD, Hassan SS, Carey VJ. Targeted expression profiling by RNA-Seq improves detection of cellular dynamics during pregnancy and identifies a role for T cells in term parturition. Sci Rep; Sci Rep. 2019 Jan 29;9(1):848.
  • Tarca AL, Romero R, Gudicha DW, Erez O, Hernandez-Andrade E, Yeo L, Bhatti G, Pacora P, Maymon E, Hassan SS. A new customized fetal growth standard for African American women: the PRB/NICHD Detroit study. Am J Obstet Gynecol; 218(2S):S679-S91 e4, 2018.
  • Tarca AL, Lauria M, Unger M, Bilal E, Boue S, Kumar Dey K, Hoeng J, Koeppl H, Martin F, Meyer P, Nandy P, Norel R, Peitsch M, Rice JJ, Romero R, Stolovitzky G, Talikka M, Xiang Y, Zechner C, Collaborators ID. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge. Bioinformatics;29(22):2892-9, 2013.
  • Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, Kim CJ, Kusanovic JP, Romero R. A novel signaling pathway impact analysis. Bioinformatics;25(1):75-82, 2009.


  • Bioinformatics: theory and practice (MGG 7050)
  • Bioinformatics I (CSC 7301)
  • Bioinformatics II (CSC 7410)
  • Computer Applications in Molecular Genetics (MBG 8680)